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Import py26-scikits_learn-0.5 as wip/py-scikits_learn.

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A set of python modules for machine learning and data mining
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Kamel Ibn Aziz Derouiche 2011-01-17 22:17:27 +00:00 committed by Thomas Klausner
parent f19ba7e07d
commit ea96ee195b
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py-scikits_learn/DESCR Normal file
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A set of python modules for machine learning and data mining

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py-scikits_learn/Makefile Normal file
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# $NetBSD: Makefile,v 1.1.1.1 2011/01/17 22:17:27 jihbed Exp $
#
DISTNAME= scikits.learn-0.5
EGG_NAME= scikits.learn-0.5
PKGNAME= ${PYPKGPREFIX}-scikits_learn-0.5
CATEGORIES= math
MASTER_SITES= http://garr.dl.sourceforge.net/project/scikit-learn/
MAINTAINER= jihbed.research@gmail.com
HOMEPAGE= http://scikit-learn.sourceforge.net/
COMMENT= Set of python modules for machine learning and data mining
LICENSE= modified-bsd
#DEPENDS+= ${PYPKGPREFIX}-scipy>=0.7.0:../../math/py-scipy
PKG_DESTDIR_SUPPORT= user-destdir
USE_LANGUAGES= c c++ fortran
.include "../../graphics/py-matplotlib/buildlink3.mk"
.include "../../lang/python/egg.mk"
.include "../../math/py-numpy/buildlink3.mk"
.include "../../mk/bsd.pkg.mk"

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@comment $NetBSD: PLIST,v 1.1.1.1 2011/01/17 22:17:27 jihbed Exp $
${PYSITELIB}/scikits.learn-0.5-py2.6-nspkg.pth
${PYSITELIB}/scikits.learn-0.5-py2.6.egg-info/PKG-INFO
${PYSITELIB}/scikits.learn-0.5-py2.6.egg-info/SOURCES.txt
${PYSITELIB}/scikits.learn-0.5-py2.6.egg-info/dependency_links.txt
${PYSITELIB}/scikits.learn-0.5-py2.6.egg-info/namespace_packages.txt
${PYSITELIB}/scikits.learn-0.5-py2.6.egg-info/not-zip-safe
${PYSITELIB}/scikits.learn-0.5-py2.6.egg-info/top_level.txt
${PYSITELIB}/scikits/__init__.py
${PYSITELIB}/scikits/learn/__init__.py
${PYSITELIB}/scikits/learn/__init__.pyc
${PYSITELIB}/scikits/learn/__init__.pyo
${PYSITELIB}/scikits/learn/ball_tree.so
${PYSITELIB}/scikits/learn/base.py
${PYSITELIB}/scikits/learn/base.pyc
${PYSITELIB}/scikits/learn/base.pyo
${PYSITELIB}/scikits/learn/cluster/__init__.py
${PYSITELIB}/scikits/learn/cluster/__init__.pyc
${PYSITELIB}/scikits/learn/cluster/__init__.pyo
${PYSITELIB}/scikits/learn/cluster/affinity_propagation_.py
${PYSITELIB}/scikits/learn/cluster/affinity_propagation_.pyc
${PYSITELIB}/scikits/learn/cluster/affinity_propagation_.pyo
${PYSITELIB}/scikits/learn/cluster/k_means_.py
${PYSITELIB}/scikits/learn/cluster/k_means_.pyc
${PYSITELIB}/scikits/learn/cluster/k_means_.pyo
${PYSITELIB}/scikits/learn/cluster/mean_shift_.py
${PYSITELIB}/scikits/learn/cluster/mean_shift_.pyc
${PYSITELIB}/scikits/learn/cluster/mean_shift_.pyo
${PYSITELIB}/scikits/learn/cluster/spectral.py
${PYSITELIB}/scikits/learn/cluster/spectral.pyc
${PYSITELIB}/scikits/learn/cluster/spectral.pyo
${PYSITELIB}/scikits/learn/cluster/tests/__init__.py
${PYSITELIB}/scikits/learn/cluster/tests/__init__.pyc
${PYSITELIB}/scikits/learn/cluster/tests/__init__.pyo
${PYSITELIB}/scikits/learn/cluster/tests/common.py
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${PYSITELIB}/scikits/learn/cluster/tests/test_affinity_propagation.py
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${PYSITELIB}/scikits/learn/cluster/tests/test_mean_shift.py
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${PYSITELIB}/scikits/learn/cluster/tests/test_mean_shift.pyo
${PYSITELIB}/scikits/learn/cluster/tests/test_spectral.py
${PYSITELIB}/scikits/learn/cluster/tests/test_spectral.pyc
${PYSITELIB}/scikits/learn/cluster/tests/test_spectral.pyo
${PYSITELIB}/scikits/learn/covariance/__init__.py
${PYSITELIB}/scikits/learn/covariance/__init__.pyc
${PYSITELIB}/scikits/learn/covariance/__init__.pyo
${PYSITELIB}/scikits/learn/covariance/covariance.py
${PYSITELIB}/scikits/learn/covariance/covariance.pyc
${PYSITELIB}/scikits/learn/covariance/covariance.pyo
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${PYSITELIB}/scikits/learn/covariance/ledoit_wolf.pyo
${PYSITELIB}/scikits/learn/covariance/tests/__init__.py
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${PYSITELIB}/scikits/learn/cross_val.py
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${PYSITELIB}/scikits/learn/datasets/__init__.py
${PYSITELIB}/scikits/learn/datasets/__init__.pyc
${PYSITELIB}/scikits/learn/datasets/__init__.pyo
${PYSITELIB}/scikits/learn/datasets/base.py
${PYSITELIB}/scikits/learn/datasets/base.pyc
${PYSITELIB}/scikits/learn/datasets/base.pyo
${PYSITELIB}/scikits/learn/datasets/data/diabetes.csv
${PYSITELIB}/scikits/learn/datasets/data/digits.csv.gz
${PYSITELIB}/scikits/learn/datasets/data/iris.csv
${PYSITELIB}/scikits/learn/datasets/descr/digits.rst
${PYSITELIB}/scikits/learn/datasets/descr/iris.rst
${PYSITELIB}/scikits/learn/datasets/mlcomp.py
${PYSITELIB}/scikits/learn/datasets/mlcomp.pyc
${PYSITELIB}/scikits/learn/datasets/mlcomp.pyo
${PYSITELIB}/scikits/learn/datasets/samples_generator.py
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${PYSITELIB}/scikits/learn/datasets/setup.py
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${PYSITELIB}/scikits/learn/datasets/setup.pyo
${PYSITELIB}/scikits/learn/externals/__init__.py
${PYSITELIB}/scikits/learn/externals/__init__.pyc
${PYSITELIB}/scikits/learn/externals/__init__.pyo
${PYSITELIB}/scikits/learn/externals/joblib/__init__.py
${PYSITELIB}/scikits/learn/externals/joblib/__init__.pyc
${PYSITELIB}/scikits/learn/externals/joblib/__init__.pyo
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${PYSITELIB}/scikits/learn/externals/joblib/my_exceptions.py
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${PYSITELIB}/scikits/learn/externals/joblib/numpy_pickle.py
${PYSITELIB}/scikits/learn/externals/joblib/numpy_pickle.pyc
${PYSITELIB}/scikits/learn/externals/joblib/numpy_pickle.pyo
${PYSITELIB}/scikits/learn/externals/joblib/parallel.py
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${PYSITELIB}/scikits/learn/externals/joblib/test/__init__.py
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${PYSITELIB}/scikits/learn/externals/joblib/test/common.py
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${PYSITELIB}/scikits/learn/feature_extraction/__init__.py
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6
py-scikits_learn/distinfo Normal file
View file

@ -0,0 +1,6 @@
$NetBSD: distinfo,v 1.1.1.1 2011/01/17 22:17:27 jihbed Exp $
SHA1 (scikits.learn-0.5.tar.gz) = 6c8c92f3a83b83388a40c894a5b742ba39166467
RMD160 (scikits.learn-0.5.tar.gz) = 21597b9c9707fa9eb1ca6f8cdad2c79af3394914
Size (scikits.learn-0.5.tar.gz) = 779881 bytes
SHA1 (patch-aa) = e06955a0632920b8b8917eec3315f3f1b17c142f

42
py-scikits_learn/patches/patch-aa Normal file
View file

@ -0,0 +1,42 @@
$NetBSD: patch-aa,v 1.1.1.1 2011/01/17 22:17:27 jihbed Exp $
--- scikits/learn/utils/src/cholesky_delete.c.orig 2011-01-04 18:42:32.000000000 +0100
+++ scikits/learn/utils/src/cholesky_delete.c 2011-01-04 18:43:10.000000000 +0100
@@ -18,27 +18,27 @@
double c, s;
/* delete row go_out */
- double * _L = L + (go_out * m);
+ double * L1 = L + (go_out * m);
int i;
for (i = go_out; i < n - 1; ++i) {
- cblas_dcopy (i + 2, _L + m , 1, _L, 1);
- _L += m;
+ cblas_dcopy (i + 2, L1 + m , 1, L1, 1);
+ L1 += m;
}
- _L = L + (go_out * m);
+ L1 = L + (go_out * m);
for (i=go_out; i < n - 1; ++i) {
- cblas_drotg (_L + i, _L + i + 1, &c, &s);
- if (_L[i] < 0) {
+ cblas_drotg (L1 + i, L1 + i + 1, &c, &s);
+ if (L1[i] < 0) {
/* Diagonals cannot be negative */
- _L[i] = copysign(_L[i], 1.0);
+ L1[i] = copysign(L1[i], 1.0);
c = -c;
s = -s;
}
- _L[i+1] = 0.; /* just for cleanup */
- _L += m;
+ L1[i+1] = 0.; /* just for cleanup */
+ L1 += m;
- cblas_drot (n - (i + 2), _L + i, m, _L + i + 1,
+ cblas_drot (n - (i + 2), L1 + i, m, L1 + i + 1,
m, c, s);
}